The individual|collective dialectic in the learning organization
Bibliographic record
Abstract
Purpose – The purpose of this paper is to answer two interrelated questions: “Who learns and how in the learning organization?”. By implication, many theories of the learning organization are adressed that are based on a static and erroneous separation of individual and collective. Design/methodology/approach – Four episodes from a larger case study exemplify the theoretical arguments. These were based on a longitudinal ethnographic study of a salmon hatchery and the public‐sector organization to which the former was accountable. Conceptual framework is strongly dialectical: in their actions individuals concretely reproduce the organization and, when actions vary, realize it in novel forms; organizations therefore presuppose individuals that concretely produce them. However, without an organization, there would be no aim or orientation to individual actions to speak of in the first instance. Findings – The paper finds that individuals learn, through the production of socio‐material resources, notions of organizations which are not abstract. These resources increase action possibilities for the collective, whether realized concretely or not. Expansive learning in individuals is co‐constitutive of learning in organizations and decreasing interest in individual learning constitutes decreased levels of action possibilities for the collective. Research limitations/implications – The paper shows that using this framework, it becomes problematic to separate individual and collective learning. Originality/value – The paper shows that access to participation by all members is a key component as are affordances given by the organization for the development of individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.064 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".